Knowledge Base Repository
In addition to research papers, the Design Society is developing several valuable resources for those interested in the study of design. These include a repository of PhD theses, a library of case studies and transcripts of design activities, and an archive of our newsletters. Please note that these resources are accessible exclusively to Design Society members.
Utilisation Of Production Feedback For ML-Based Geometric Deviation Prediction
Brünnhäußer, Jörg; Dziubinska, Magdalena; Zimmermann, Thomas; Lünnemann, Pascal; Lindow, Kai
Type:
Year:
2026
Editor:
Juuti, T.; Karhunen, V; Vanhatalo, M.; Lehtonen, T.;Kopra, M-J.
Author:
Series:
NordDESIGN
Institution:
Fraunhofer IPK, Germany
Page(s):
411-420
DOI number:
ISBN:
978-1-912254-21-7
ISSN:
NA
Abstract:
This paper presents a proof of concept approach for predicting geometric deviations of CAD designs after their production. This could help designers to recognize possible quality issues or deviations as early as possible. Several machine learning models are trained on designs and CT scanned as manufactured parts produced by different AM processes. Results show that the used models and features have minor impact compared to the composition of the training data. The approach demonstrates the feasibility of ML based deviation prediction to support earlier and more informed design decisions.
Keywords:
